Performs spatial tests on spatial cytometry data.
Usage
spicy(
cells,
condition,
subject = NULL,
covariates = NULL,
imageID = "imageID",
cellType = "cellType",
spatialCoords = c("x", "y"),
r = NULL,
sigma = NULL,
from = NULL,
to = NULL,
alternateResult = NULL,
cores = 1,
minLambda = 0.05,
weights = TRUE,
weightsByPair = FALSE,
weightFactor = 1,
window = "convex",
window.length = NULL,
edgeCorrect = TRUE,
includeZeroCells = FALSE,
verbose = FALSE,
BPPARAM = BiocParallel::SerialParam(),
imageIDCol = imageID,
cellTypeCol = cellType,
spatialCoordCols = spatialCoords,
nCores = cores,
Rs = r,
...
)Arguments
- cells
A SummarizedExperiment or data frame that contains at least the variables x and y, giving the location coordinates of each cell, and cellType.
- condition
A character specifying which column which contains the condition or `Surv` objects.
- subject
Vector of subject IDs corresponding to each image if cells is a data frame.
- covariates
Vector of covariate names that should be included in the mixed effects model as fixed effects.
- imageID
The name of the imageID column if using a SingleCellExperiment or SpatialExperiment.
- cellType
The name of the cellType column if using a SingleCellExperiment or SpatialExperiment.
- spatialCoords
The names of the spatialCoords column if using a SingleCellExperiment.
- r
A vector of the radii that the measures of association should be calculated over.
- sigma
A numeric variable used for scaling when fitting inhomogenous L-curves.
- from
vector of cell types which you would like to compare to the to vector.
- to
vector of cell types which you would like to compare to the from vector.
- alternateResult
A pairwise association statistic between each combination of celltypes in each image.
- cores
Number of cores to use for parallel processing or a BiocParallel MulticoreParam or SerialParam object.
- minLambda
Minimum value density for scaling when fitting inhomogeneous L-curves.
- weights
logical indicating whether to include weights based on cell counts.
- weightsByPair
logical indicating whether weights should be calculated for each cell type pair.
- weightFactor
numeric that controls the convexity of the weight function.
- window
Should the window around the regions be 'square', 'convex' or 'concave'.
- window.length
A tuning parameter for controlling the level of concavity when estimating concave windows.
- edgeCorrect
A logical indicating whether to perform edge correction.
- includeZeroCells
A logical indicating whether to include cells with zero counts in the pairwise association calculation.
- verbose
logical indicating whether to output messages.
- BPPARAM
{DEPRECATED} A BiocParallel MulticoreParam or SerialParam object.
- imageIDCol
{DEPRECATED} The name of the imageID column if using a SingleCellExperiment or SpatialExperiment.
- cellTypeCol
{DEPRECATED} The name of the cellType column if using a SingleCellExperiment or SpatialExperiment.
- spatialCoordCols
{DEPRECATED} The names of the spatialCoords column if using a SingleCellExperiment.
- nCores
{DEPRECATED} Number of cores to use for parallel processing or a BiocParallel MulticoreParam or SerialParam object.
- Rs
{DEPRECATED} A vector of the radii that the measures of association should be calculated over.
- ...
Other options
Examples
data("diabetesData")
# Test with random effect for patient on a pairwise combination of cell
# types.
spicy(diabetesData,
condition = "stage", subject = "case",
from = "Tc", to = "Th"
)
#> Skipping argument checks as `getPairwise()` is being called within `spicy()`
#>
#> Number of cell type pairs: 1
#> Number of differentially localised cell type pairs:
#> [1] 0
# Test all pairwise combinations of cell types without random effect of
# patient.
if (FALSE) { # \dontrun{
spicyTest <- spicy(diabetesData, condition = "stage", subject = "case")
} # }
# Test all pairwise combination of cell types with random effect of patient.
if (FALSE) { # \dontrun{
spicy(diabetesData, condition = "condition", subject = "subject")
} # }